As part of the U.S. Geological Survey (USGS) and Department of Defense Task Force for Business and Stability Operations (TFBSO) natural resources revitalization activities in Afghanistan (Peters and others, 2011), three new datasets have been collected, compiled, and analyzed. These data have been used to more fully evaluate the areas of interest (AOIs; fig. 1 ) where, on the basis of previous U.S.S.R. and Afghanistan studies, the opportunity for early economic development of a number of different mineral, commodity, and deposit types had been identified (Peters and others, 2007; Peters and others, 2011). The new data compilations include (1) regional magnetic and gravity data for use in the characterization of subsurface composition and structure (Sweeney and others, 2006a,b; Ashan and others, 2007; Sweeney and others, 2007; Ashan and others, 2008; Shenwary and others, 2011), (2) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data to identify and evaluate surficial alteration patterns related to industrial minerals and other selected targets, and (3) HyMap imaging spectrometer data for characterization and mapping of surficial mineralogy (Cocks and others, 1998; Kokaly and others, 2008; Peters and others, 2011). These datasets have served as fundamental building blocks for the resource evaluation by Peters and others (2011).
During the independent analysis of the geophysical, ASTER, and imaging spectrometer (HyMap) data by USGS scientists, previously unrecognized targets of potential mineralization were identified using evaluation criteria most suitable to the individual dataset. These anomalous zones offer targets of opportunity that warrant additional field verification. This report describes the standards used to define the anomalies, summarizes the results of the evaluations for each type of data, and discusses the importance and implications of regions of anomaly overlap between two or three of the datasets.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111229","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey","usgsCitation":"King, T.V.V., Johnson, M.R., Hubbard, B.E., and Drenth, B.J., eds., 2011, Identification of mineral resources in Afghanistan—Detecting and mapping resource anomalies in prioritized areas using geophysical and remote sensing (ASTER and HyMap) data: U.S. Geological Survey Open-File Report 2011–1229, 327 p.","productDescription":"Report: vi, 327 p.; Dataset; 4 Figures","additionalOnlineFiles":"Y","costCenters":[{"id":537,"text":"Projects in Afghanistan","active":false,"usgs":true}],"links":[{"id":116565,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2011/1229/coverthb.png"},{"id":370552,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2011/1229/ofr20111229.pdf","text":"Report","size":"193 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1229"},{"id":370553,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2011/1229/report/figures/GEO.zip","text":"Geophysical figures","size":"19.7 MB","linkFileType":{"id":6,"text":"zip"}},{"id":370554,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2011/1229/report/figures/AST.zip","text":"ASTER figures","size":"95.0 MB","linkFileType":{"id":6,"text":"zip"}},{"id":370555,"rank":5,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2011/1229/report/figures/HSD.zip","text":"HyMap hyperspectral figures","size":"251 MB","linkFileType":{"id":6,"text":"zip"}},{"id":370556,"rank":6,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2011/1229/report/figures/Map.zip","text":"Maps","size":"4.65 MB","linkFileType":{"id":6,"text":"zip"}},{"id":370557,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/of/2011/1229/ofr20111229_dataset.zip","size":"200 KB","linkFileType":{"id":6,"text":"zip"}}],"country":"Afghanistan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60,29.5 ], [ 60,38.5 ], [ 73.5,38.5 ], [ 73.5,29.5 ], [ 60,29.5 ] ] ] } } ] }","contact":"Visit the USGS Projects in Afghanistan website
","tableOfContents":"Within the last decade, advances in the acquisition, processing and transmission of data from real-time seismic monitoring systems has contributed to the growth in the number structures instrumented with such systems. An equally important factor for such growth can be attributed to the demands by stakeholders to find rapid answers to important questions related to the functionality (or “state of health”) of structures during and immediately following a seismic event. Hence, rapid and accurate assessment of the damage condition or performance of a building or a lifeline structure is of paramount importance to stakeholders, including owners, leasers, permanent and/or temporary occupants, users of infrastructures, city officials and rescue teams that are concerned with safety of those in the building, and those that may be affected in nearby buildings and infrastructures. In earlier papers, we described how observed data from sensors deployed in structures can be configured to establish seismic health monitoring of structures. In these configurations, drift ratios are the main parametric indicator of damage condition of a building. The process described for buildings can be applied directly for bridges as well. For bridges, the term, “drift ratio” is not generally used; however, relative displacements of critical elements of a bridge can be construed as such. While real-time data from structural arrays indicate that these methods are reliable and provide requisite information for owners and other parties to make informed decisions and to choose among pre-defined actions following significant events, there are several issues related to data ownership, transmission and archiving. This paper examines the real-time seismic monitoring systems deployed mainly in the United States, with particular attention to data issues – handling, dissemination, storage, and archiving. In most cases, due to the numerous channels involved, the deployments in each one of the real-time structures can be considered to be an individual array. Two detailed cases are described that demonstrate the variability in data ownership and dissemination.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Earthquake data in engineering seismology: Predictive models, data management and networks","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer Link","doi":"10.1007/978-94-007-0152-6_16","usgsCitation":"Celebi, M., 2011, Real-time seismic monitoring of structures: Data handling and case studies, chap. of Earthquake data in engineering seismology: Predictive models, data management and networks, v. 14, p. 235-245, https://doi.org/10.1007/978-94-007-0152-6_16.","productDescription":"11 p.","startPage":"235","endPage":"245","ipdsId":"IP-017436","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":364937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","noUsgsAuthors":false,"publicationDate":"2010-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Celebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":200969,"corporation":false,"usgs":true,"family":"Celebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[],"preferred":true,"id":849688,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70203883,"text":"70203883 - 2011 - Arsenic in Chinese coals: Distribution, modes of occurrence, and environmental effects","interactions":[],"lastModifiedDate":"2019-06-18T18:27:30","indexId":"70203883","displayToPublicDate":"2019-06-18T18:25:33","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"title":"Arsenic in Chinese coals: Distribution, modes of occurrence, and environmental effects","docAbstract":"Arsenic, one of the most hazardous elements occurring in coals, can be released to the environment during coal processing and combustion. Based on the available literature and published results obtained in our laboratory, the content, distribution and the modes of occurrence of As in Chinese coals, and its environmental and impacts are reviewed in this article. With the 4763 sets of data (from the literature) rearranged, the arithmetic mean As concentration of each province and weighted mean As concentration of the entire country (using the expected coal reserves as the weighting factor) were calculated. The weighted mean As concentration in Chinese coals is 3.18 mg/kg, with As concentration increasing from northern China to southern China. The As concentration in coal varies with coal-forming ages and coal ranks. Arsenic has several modes of occurrence in coals. According to results obtained by other studies and our own experiments, As is mainly associated with mineral matter (such as pyrite and other sulfide minerals) in coals, although a significant amount of arsenic is associated with organic matter. The accumulation of As in coal is controlled by many geological factors during coal-forming processes, including plant decomposition, sedimentary environments, and epigenetic hydrothermal activity. During the combustion of coal, As is released to the air, water, and soil, causing serious environmental pollution. More than 45% of the coal consumed in China is utilized by power plants, and it is estimated that nearly 522 tonnes, 21 tonnes and 252 tonnes of As are emitted into the atmosphere by industries, residential buildings and coal-fired power plants, respectively, every year.
","language":"English","publisher":"Science of the Total Environment","doi":"10.1016/j.scitotenv.2011.10.026","usgsCitation":"Kang, Y., and Liu, G., 2011, Arsenic in Chinese coals: Distribution, modes of occurrence, and environmental effects, v. 412, p. 1-13, https://doi.org/10.1016/j.scitotenv.2011.10.026.","productDescription":"13 p.","startPage":"1","endPage":"13","costCenters":[],"links":[{"id":364805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"412","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kang, Y.","contributorId":54431,"corporation":false,"usgs":true,"family":"Kang","given":"Y.","email":"","affiliations":[],"preferred":false,"id":764581,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Guijian","contributorId":216351,"corporation":false,"usgs":false,"family":"Liu","given":"Guijian","email":"","affiliations":[],"preferred":false,"id":764582,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70101104,"text":"70101104 - 2011 - Strong ground motion in Port-au-Prince, Haiti, during the M7.0 12 January 2010 Haiti earthquake","interactions":[],"lastModifiedDate":"2017-01-19T12:02:48","indexId":"70101104","displayToPublicDate":"2016-12-01T12:53:51","publicationYear":"2011","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Strong ground motion in Port-au-Prince, Haiti, during the M7.0 12 January 2010 Haiti earthquake","docAbstract":"Since the days of MacArthur, three-dimensional (3-D) structural information on the environment has fundamentally transformed scientific understanding of ecological phenomena (MacArthur and MacArthur 1961). Early data on ecosystem structure were painstakingly laborious to collect. However, as reviewed and reported in recent volumes of Frontiers(eg Vierling et al. 2008; Asner et al.2011), advances in light detection and ranging (LiDAR) remote-sensing technology provide quantitative and repeatable measurements of 3-D ecosystem structure that enable novel ecological insights at scales ranging from the plot, to the landscape, to the globe. Indeed, annual publication of studies using LiDAR to interpret ecological phenomena increased 17-fold during the past decade, with over 180 new studies appearing in 2010 (ISI Web of Science search conducted on 23 Mar 2011: [{lidar AND ecol*} OR {lidar AND fores*} OR {lidar AND plant*}]).
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/11.WB.009","usgsCitation":"Vierling, L.A., Martinuzzi, S., Asner, G.P., Stoker, J.M., and Johnson, B.R., 2011, LiDAR: Providing structure : Frontiers in Ecology and the Environment, v. 9, no. 5, p. 261-262, https://doi.org/10.1890/11.WB.009.","productDescription":"2 p.","startPage":"261","endPage":"262","ipdsId":"IP-028995","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":333462,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5881dedce4b01192927d9f93","contributors":{"authors":[{"text":"Vierling, Lee A.","contributorId":169443,"corporation":false,"usgs":false,"family":"Vierling","given":"Lee","email":"","middleInitial":"A.","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":659028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martinuzzi, Sebastián","contributorId":68180,"corporation":false,"usgs":true,"family":"Martinuzzi","given":"Sebastián","affiliations":[],"preferred":false,"id":659029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Asner, Gregory P.","contributorId":25393,"corporation":false,"usgs":false,"family":"Asner","given":"Gregory","email":"","middleInitial":"P.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":659030,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":true,"id":659031,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Brian R.","contributorId":178466,"corporation":false,"usgs":false,"family":"Johnson","given":"Brian","email":"","middleInitial":"R.","affiliations":[{"id":16880,"text":"National Ecological Observatory Network (NEON), 1685 38th St., Boulder, CO 80301, USA","active":true,"usgs":false}],"preferred":false,"id":659032,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70171362,"text":"70171362 - 2011 - Distribution and abundance of stream fishes in relation to barriers: implications for monitoring stream recovery after barrier removal","interactions":[],"lastModifiedDate":"2016-05-27T14:12:14","indexId":"70171362","displayToPublicDate":"2016-01-18T05:15:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Distribution and abundance of stream fishes in relation to barriers: implications for monitoring stream recovery after barrier removal","docAbstract":"Dams are ubiquitous in coastal regions and have altered stream habitats and the distribution and abundance of stream fishes in those habitats by disrupting hydrology, temperature regime and habitat connectivity. Dam removal is a common restoration tool, but often the response of the fish assemblage is not monitored rigorously. Sedgeunkedunk Stream, a small tributary to the Penobscot River (Maine, USA), has been the focus of a restoration effort that includes the removal of two low-head dams. In this study, we quantified fish assemblage metrics along a longitudinal gradient in Sedgeunkedunk Stream and also in a nearby reference stream. By establishing pre-removal baseline conditions and associated variability and the conditions and variability immediately following removal, we can characterize future changes in the system associated with dam removal. Over 2 years prior to dam removal, species richness and abundance in Sedgeunkedunk Stream were highest downstream of the lowest dam, lowest immediately upstream of that dam and intermediate farther upstream; patterns were similar in the reference stream. Although seasonal and annual variation in metrics within each site was substantial, the overall upstream-to-downstream pattern along the stream gradient was remarkably consistent prior to dam removal. Immediately after dam removal, we saw significant decreases in richness and abundance downstream of the former dam site and a corresponding increase in fish abundance upstream of the former dam site. No such changes occurred in reference sites. Our results show that by quantifying baseline conditions in a small stream before restoration, the effects of stream restoration efforts on fish assemblages can be monitored successfully. These data set the stage for the long-term assessment of Sedgeunkedunk Stream and provide a simple methodology for assessment in other restoration projects.
","language":"English","publisher":"Wiley Online","doi":"10.1002/rra.1572","usgsCitation":"Zydlewski, J.D., Coghlan, S.M., Gardner, C., and Saunders, R., 2011, Distribution and abundance of stream fishes in relation to barriers: implications for monitoring stream recovery after barrier removal: River Research and Applications, v. 29, no. 1, p. 65-78, https://doi.org/10.1002/rra.1572.","productDescription":"13 p.","startPage":"65","endPage":"78","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026736","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":321835,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","county":"Penobscot","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.99757385253906,\n 44.56454494930599\n ],\n [\n -68.99757385253906,\n 44.800839614637205\n ],\n [\n -68.52104187011719,\n 44.800839614637205\n ],\n [\n -68.52104187011719,\n 44.56454494930599\n ],\n [\n -68.99757385253906,\n 44.56454494930599\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"29","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2011-08-22","publicationStatus":"PW","scienceBaseUri":"57496faee4b07e28b665cc56","contributors":{"authors":[{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":630717,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coghlan, Stephen M. Jr.","contributorId":169678,"corporation":false,"usgs":false,"family":"Coghlan","given":"Stephen","suffix":"Jr.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":630739,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gardner, C.","contributorId":57402,"corporation":false,"usgs":true,"family":"Gardner","given":"C.","affiliations":[],"preferred":false,"id":630740,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saunders, R.","contributorId":94243,"corporation":false,"usgs":true,"family":"Saunders","given":"R.","affiliations":[],"preferred":false,"id":630741,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70042134,"text":"70042134 - 2011 - LANDFIRE 2001 and 2008 Refresh Geographic Area Report--Pacific Southwest","interactions":[],"lastModifiedDate":"2017-01-18T13:42:44","indexId":"70042134","displayToPublicDate":"2015-07-13T12:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"LANDFIRE 2001 and 2008 Refresh Geographic Area Report--Pacific Southwest","docAbstract":"The LANDFIRE National project (LF_1.0.0) was successfully completed in 2009. The goal of LANDFIRE National was to generate consistent 2001 vintage 30 meter spatial data sets for all 50 states for fire and other natural resource applications. This report highlights results from the continuation of LANDFIRE as a program to update the spatial data layers through 2008. The focus of this phase of the program was to improve the data products and account for vegetation change across the landscape caused by wildland fire, fuel and vegetation treatments, and (or) management. In addition, changes caused by insects and disease, storms, invasive plants, and other natural or anthropogenic events were incorporated when appropriate data were available. This report describes the LANDFIRE 2001/2008 Refresh effort to update existing map layers to reflect more current conditions, focusing primarily on vegetation changes. The effort incorporated user feedback and new data, producing two comprehensive Refresh data product sets:
\n
1. LANDFIRE 2001 Refresh (LF_1.0.5) enhanced LANDFIRE map layers by incorporating user feedback and additional data to provide a foundation to update data to 2008. It was also designed to provide users with a data set to help facilitate comparisons between 2001 and 2008 (i.e. Refresh LF_1.1.0) data sets.
2. LANDFIRE 2008 Refresh (LF_1.1.0) updated map layers to reflect vegetation changes and disturbances that occurred between 1999 and 2008.
\n
In this report, we (1) address the background and provide details pertaining to why there are two Refresh data sets, (2) explain the requirements, planning, and procedures behind the completion and delivery of the updated products for each of the data product sets, (3) show and describe results, and (4) provide case studies illustrating the performance of LANDFIRE National, LANDFIRE 2001 Refresh and LANDFIRE 2008 Refresh (LF_1.1.0) data products on some example wildland fires.
On June 29, 2009, NASA and the Ministry of Economy, Trade and Industry (METI) of Japan released a Global Digital Elevation Model (GDEM) to users worldwide at no charge as a contribution to the Global Earth Observing System of Systems (GEOSS). This “version 1” ASTER GDEM (GDEM1) was compiled from over 1.2 million scenebased DEMs covering land surfaces between 83°N and 83°S latitudes. A joint U.S.-Japan validation team assessed the accuracy of the GDEM1, augmented by a team of 20 cooperators. The GDEM1 was found to have an overall accuracy of around 20 meters at the 95% confidence level. The team also noted several artifacts associated with poor stereo coverage at high latitudes, cloud contamination, water masking issues and the stacking process used to produce the GDEM1 from individual scene-based DEMs (ASTER GDEM Validation Team, 2009). Two independent horizontal resolution studies estimated the effective spatial resolution of the GDEM1 to be on the order of 120 meters.
\nA second version of the ASTER GDEM (GDEM2) is scheduled for release by NASA and METI in mid-October, 2011. Improvements in the GDEM2 result from acquiring 260,000 additional scenes to improve coverage, a smaller correlation kernel to yield higher spatial resolution, and improved water masking. As with the GDEM1, the GDEM2 validation was performed by the U.S. and Japanese partners. Vertical accuracy assessments included a comparison of the GDEM2 against absolute geodetic references over the Conterminous US (CONUS), against national elevation grids over the US and Japan, against the Shuttle Radar Topography Mission (SRTM) 1 arc-second elevation grids over the US and 20 sites around the globe, and against space borne laser altimeter data globally. Horizontal accuracy assessments were conducted as part of the Japan and the global SRTM studies, and horizontal resolution studies were conducted in both Japan and the US. Each group documented changes in artifacts in GDEM2 due to processing improvements.
\nThe absolute vertical accuracy study found the GDEM2 to be within -0.20 meters on average when compared against 18,000 geodetic control points over the CONUS, with an accuracy of 17 meters at the 95% confidence level. The Japan study noted the GDEM2 differed from the 10-meter national elevation grid by -0.7 meters over bare areas, and by 7.4 meters over forested areas. Similarly, the CONUS study noted the GDEM2 to be about 8 meters above the 1 arc-second NED over most forested areas, and more than a meter below NED over bare areas. The global altimeter study found the GDEM2 to be on average within 3 meters of altimeter-derived control, and also documented sensitivity to tree canopy height. The Japan study noted that the horizontal displacement in GDEM1 of 0.95 pixels was reduced to 0.23 pixels in GDEM2. Both teams noted improvements in horizontal resolution, between 71 and 82 meters, comparable to the SRTM 1 arc second elevation model, but at the cost of some increased noise. The number of voids and artifacts noted in GDEM1 were substantially reduced in GDEM2, and in some areas virtually eliminated.
\nBased on these findings, the GDEM validation team recommends the release of the GDEM2 to the public, acknowledging that, while vastly improved, some artifacts still exist which could affect its utility in certain applications.
","language":"English","publisher":"NASA","usgsCitation":"Tachikawa, T., Kaku, M., Iwasaki, A., Gesch, D.B., Oimoen, M.J., Zhang, Z., Danielson, J.J., Krieger, T., Curtis, B., Haase, J., Abrams, M., and Carabajal, C., 2011, ASTER Global Digital Elevation Model Version 2 - summary of validation results (2), 27 p.","productDescription":"27 p","numberOfPages":"27","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-032819","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":310885,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":310884,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://asterweb.jpl.nasa.gov/gdem.asp"}],"edition":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56389741e4b0d6133fe72f94","contributors":{"compilers":[{"text":"Meyer, Dave","contributorId":149614,"corporation":false,"usgs":false,"family":"Meyer","given":"Dave","email":"","affiliations":[],"preferred":false,"id":578959,"contributorType":{"id":3,"text":"Compilers"},"rank":1}],"authors":[{"text":"Tachikawa, Tetushi","contributorId":149604,"corporation":false,"usgs":false,"family":"Tachikawa","given":"Tetushi","email":"","affiliations":[],"preferred":false,"id":578947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaku, Manabu","contributorId":149605,"corporation":false,"usgs":false,"family":"Kaku","given":"Manabu","email":"","affiliations":[],"preferred":false,"id":578948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iwasaki, Akira","contributorId":149606,"corporation":false,"usgs":false,"family":"Iwasaki","given":"Akira","email":"","affiliations":[],"preferred":false,"id":578949,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":578950,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Oimoen, Michael J. 0000-0003-3611-6227 oimoen@usgs.gov","orcid":"https://orcid.org/0000-0003-3611-6227","contributorId":4757,"corporation":false,"usgs":true,"family":"Oimoen","given":"Michael","email":"oimoen@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":578951,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zhang, Z.","contributorId":47505,"corporation":false,"usgs":true,"family":"Zhang","given":"Z.","email":"","affiliations":[],"preferred":false,"id":578952,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":578953,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Krieger, Tabatha","contributorId":149608,"corporation":false,"usgs":false,"family":"Krieger","given":"Tabatha","email":"","affiliations":[],"preferred":false,"id":578954,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Curtis, Bill","contributorId":149609,"corporation":false,"usgs":false,"family":"Curtis","given":"Bill","email":"","affiliations":[],"preferred":false,"id":578955,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Haase, Jeff","contributorId":149610,"corporation":false,"usgs":false,"family":"Haase","given":"Jeff","email":"","affiliations":[],"preferred":false,"id":578956,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Abrams, Michael","contributorId":74266,"corporation":false,"usgs":false,"family":"Abrams","given":"Michael","affiliations":[{"id":7023,"text":"Jet Propulsion Laboratory, California Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":578957,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Carabajal, C.","contributorId":46846,"corporation":false,"usgs":true,"family":"Carabajal","given":"C.","email":"","affiliations":[],"preferred":false,"id":578958,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70041534,"text":"70041534 - 2011 - Nearshore disposal of fine-grained sediment in a high-energy environment: Santa Cruz Harbor case study","interactions":[],"lastModifiedDate":"2015-10-29T14:11:23","indexId":"70041534","displayToPublicDate":"2015-07-07T09:15:00","publicationYear":"2011","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":12,"text":"Conference publication"},"title":"Nearshore disposal of fine-grained sediment in a high-energy environment: Santa Cruz Harbor case study","docAbstract":"Assessing the sustainability of International policy or urban development requires consideration of the impacts of these decisions on Ecosystem Services, or the values that humans receive from the ecosystem, including market-land price, environmental, and human well-being values. Hedonic modeling helps to identify the market land price, considering the price is determined by multiple factors affecting it. In U.S. portions of the bi-national Santa Cruz Watershed (SCW), situated at the Arizona-Sonora International border, natural amenities like the riparian corridor and green space have been documented as positive amenities that boost local real estate.
\nThe goal of this research is to isolate the effects of the US-Mexico border and known environmental or natural amenities or disamenities on housing prices in the binational watershed, while controlling for housing stock characteristics and social-environmental vulnerability. In the ultimate analysis, the mean house values within census blocks will be used to represent local housing stock. A human well-being index that measures people’s socio-environmental vulnerability for the entire SCW is in publication that is based on access to infrastructure, number of bedrooms per house and other social data from the binational census and local colonias database will also be compared. The hedonic pricing method will be applied to statistically estimate a function that relates property values to the variables described.
\nThis presentation will provide a synopsis of the quality of life and hedonics literature review used to develop this research agenda. Variables relevant for local environmental management, having significant effects on property values, will be discussed. The final results obtained from this study can be used determine the benefits of preserving or developing land binationally and will be uploaded to the Santa Cruz Watershed Ecosystem Portfolio Model (SCWEPM), an online Ecosystem Services tool, being created to promote sustainable development in the Borderlands.
","largerWorkTitle":"Proceedings of Santa Cruz River Researchers' Day","conferenceTitle":"Santa Cruz River: Researchers’ Day","conferenceDate":"March 29, 2011","conferenceLocation":"Tucson, AZ","publisher":"Sonoran Institute","usgsCitation":"Amaya, G., Norman, L.M., and Frisvold, G., 2011, Measuring the impacts of natural amenities and the US-Mexico Border, on housing values in the Santa Cruz Watershed, using spatially-weighted hedonic modeling, in Proceedings of Santa Cruz River Researchers' Day, Tucson, AZ, March 29, 2011.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-028456","costCenters":[],"links":[{"id":311050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":311049,"rank":1,"type":{"id":1,"text":"Abstract"},"url":"https://www.sonoraninstitute.org/images/stories/pdfs/Events/SCRResearchDays/scrrd%202011%20proceedings.pdf"}],"country":"Mexico, United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"563c8bbfe4b0831b7d61eff5","contributors":{"authors":[{"text":"Amaya, Gladys","contributorId":86212,"corporation":false,"usgs":true,"family":"Amaya","given":"Gladys","email":"","affiliations":[],"preferred":false,"id":579400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406 lnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":967,"corporation":false,"usgs":true,"family":"Norman","given":"Laura","email":"lnorman@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":579401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frisvold, George","contributorId":9569,"corporation":false,"usgs":true,"family":"Frisvold","given":"George","email":"","affiliations":[],"preferred":false,"id":579402,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70004523,"text":"70004523 - 2011 - Evaluation of the flathead catfish population and fishery on Lake Carl Blackwell, Oklahoma, with emphasis on the effects of noodling","interactions":[],"lastModifiedDate":"2015-11-05T11:50:04","indexId":"70004523","displayToPublicDate":"2015-07-06T09:15:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Evaluation of the flathead catfish population and fishery on Lake Carl Blackwell, Oklahoma, with emphasis on the effects of noodling","docAbstract":"I conducted a 3-year study at Lake Carl Blackwell, Oklahoma to estimate effects of various fishing gears on the flathead catfish Pylodictis olivaris population. Managers were particularly interested in the effect of handfishing or noodling on this population. I used a phone survey to assess angler effort and electrofishing and gill nets to calculate standard population metrics to assess composition of the current population. Survey data indicated that fishing effort and harvest were highest for trotlines and juglines and lowest for noodling. Size distribution of fish harvested by noodlers was not different from sizes that were available in the fishery and was similar to those fish harvested with other gears. Flathead catfish Sampled in Lake Carl Blackwell ranged in size from 38 to 1,220 mm total length, and 77% of the population was less than 508 mm (minimum legal size). Estimated total annual mortality was about 11%. Proportional size distribution (PSD) of flathead catfish for Lake Carl Blackwell indicates that about 70% of legal-sized flathead catfish were over the preferred size of 710 mm. Overall, the Lake Carl Blackwell flathead catfish population appeared healthy. There were a wide range of sizes and ages in the population, and PSD indicated a well-balanced population with many preferred and memorable-sized fish. Due to its rarity, noodling is probably not adversely influencing the population. Additionally, noodling at Lake Carl Blackwell does not appear to be as size-selective as previously thought.
","largerWorkTitle":"Conservation, Ecology, and Management of Catfish: The Second International Symposium","language":"English","publisher":"American Fisheries Society","isbn":"978-1-934874-25-7","usgsCitation":"Winkelman, D.L., 2011, Evaluation of the flathead catfish population and fishery on Lake Carl Blackwell, Oklahoma, with emphasis on the effects of noodling, chap. of Conservation, Ecology, and Management of Catfish: The Second International Symposium, 10 p.","productDescription":"10 p.","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-030292","costCenters":[],"links":[{"id":311045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":311044,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://fisheries.org/shop/54077c"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Lake Carl Blackwell","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.31071472167969,\n 36.097938036628065\n ],\n [\n -97.31071472167969,\n 36.16227046727886\n ],\n [\n -97.174072265625,\n 36.16227046727886\n ],\n [\n -97.174072265625,\n 36.097938036628065\n ],\n [\n -97.31071472167969,\n 36.097938036628065\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"563c8bbbe4b0831b7d61efea","contributors":{"editors":[{"text":"Michaletz, Paul H.","contributorId":111870,"corporation":false,"usgs":true,"family":"Michaletz","given":"Paul","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":579389,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Travnichek, Vincent H.","contributorId":111523,"corporation":false,"usgs":true,"family":"Travnichek","given":"Vincent","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":579390,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Winkelman, Dana L. 0000-0002-5247-0114 danaw@usgs.gov","orcid":"https://orcid.org/0000-0002-5247-0114","contributorId":4141,"corporation":false,"usgs":true,"family":"Winkelman","given":"Dana","email":"danaw@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":579388,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70004579,"text":"70004579 - 2011 - Merging climate and multi-sensor time-series data in real-time drought monitoring across the U.S.A.","interactions":[],"lastModifiedDate":"2018-02-21T12:56:41","indexId":"70004579","displayToPublicDate":"2015-07-05T00:15:00","publicationYear":"2011","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Merging climate and multi-sensor time-series data in real-time drought monitoring across the U.S.A.","docAbstract":"Droughts occur repeatedly in the United States resulting in billions of dollars of damage. Monitoring and reporting on drought conditions is a necessary function of government agencies at multiple levels. A team of Federal and university partners developed a drought decision- support tool with higher spatial resolution relative to traditional climate-based drought maps. The Vegetation Drought Response Index (VegDRI) indicates general canopy vegetation condition assimilation of climate, satellite, and biophysical data via geospatial modeling. In VegDRI, complementary drought-related data are merged to provide a comprehensive, detailed representation of drought stress on vegetation. Time-series data from daily polar-orbiting earth observing systems [Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS)] providing global measurements of land surface conditions are ingested into VegDRI. Inter-sensor compatibility is required to extend multi-sensor data records; thus, translations were developed using overlapping observations to create consistent, long-term data time series.
","largerWorkTitle":"34th International Symposium on Remote Sensing of Environment: The GEOSS Era: Towards Operational Environmental Monitoring","conferenceTitle":"34th International Symposium on Remote Sensing of Environment","conferenceDate":"April 10-15, 2011","conferenceLocation":"Sydney, Australia","language":"English","usgsCitation":"Brown, J.F., Miura, T., Wardlow, B., and Gu, Y., 2011, Merging climate and multi-sensor time-series data in real-time drought monitoring across the U.S.A., in 34th International Symposium on Remote Sensing of Environment: The GEOSS Era: Towards Operational Environmental Monitoring, Sydney, Australia, April 10-15, 2011, 5 p.","productDescription":"5 p.","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-027351","costCenters":[],"links":[{"id":311039,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":311040,"rank":1,"type":{"id":15,"text":"Index 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States\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"563c8bc0e4b0831b7d61eff7","contributors":{"authors":[{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":3241,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":579303,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miura, T.","contributorId":149745,"corporation":false,"usgs":false,"family":"Miura","given":"T.","email":"","affiliations":[{"id":17202,"text":"University of Hawaii, Manoa","active":true,"usgs":false}],"preferred":false,"id":579304,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wardlow, B.","contributorId":56863,"corporation":false,"usgs":false,"family":"Wardlow","given":"B.","email":"","affiliations":[{"id":12505,"text":"University of Nebraska - Lincoln","active":true,"usgs":false}],"preferred":false,"id":579305,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gu, Yingxin 0000-0002-3544-1856 ygu@usgs.gov","orcid":"https://orcid.org/0000-0002-3544-1856","contributorId":139586,"corporation":false,"usgs":true,"family":"Gu","given":"Yingxin","email":"ygu@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":579306,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70004585,"text":"sir20115004 - 2011 - Concentrations, loads, and sources of polychlorinated biphenyls, Neponset River and Neponset River Estuary, eastern Massachusetts","interactions":[],"lastModifiedDate":"2014-06-25T08:48:17","indexId":"sir20115004","displayToPublicDate":"2014-06-08T10:50:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-5004","title":"Concentrations, loads, and sources of polychlorinated biphenyls, Neponset River and Neponset River Estuary, eastern Massachusetts","docAbstract":"Polychlorinated biphenyls (PCBs) are known to contaminate the Neponset River, which flows through parts of Boston, Massachusetts, and empties into the Neponset River Estuary, an important fish-spawning area. The river is dammed and impassable to fish. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Fish and Game, Division of Ecological Restoration, Riverways Program, collected, analyzed, and interpreted PCB data from bottom-sediment, water, and (or) fish-tissue samples in 2002, 2004-2006. Samples from the Neponset River and Neponset River Estuary were analyzed for 209 PCB congeners, PCB homologs, and Aroclors. In order to better assess the overall health quality of river-bottom sediments, sediment samples were also tested for concentrations of 31 elements.
\nPCB concentrations measured in the top layers of bottom sediment ranged from 28 nanograms per gram (ng/g) just upstream of the Mother Brook confluence to 24,900 ng/g measured in Mother Brook. Concentrations of elements in bottom sediment were generally higher than background concentrations and higher than levels considered toxic to benthic organisms according to freshwater sediment-quality guidelines defined by the U.S. Environmental Protection Agency. Concentrations of dissolved PCBs in water samples collected from the Neponset River (May 13, 2005 to April 28, 2006) averaged about 9.2 nanograms per liter (ng/L) (annual average of monthly values); however, during the months of August (about 16.5 ng/L) and September (about 15.6 ng/L), dissolved PCB concentrations were greater than 14 ng/L, the U.S. Environmental Protection Agency's freshwater continuous chronic criterion for aquatic organisms. Concentrations of PCBs in white sucker (fillets and whole fish) were all greater than 2,000 ng/g wet wt, the U.S. Environmental Protection Agency's guideline for safe consumption of fish: PCB concentrations measured in fish-tissue samples collected from the Tileston and Hollingsworth and Walter Baker Impoundments were 3,490 and 2,450 ng/g wet wt (filleted) and 6,890 and 4,080 ng/g wet wt (whole fish). Total PCB-congener concentrations measured in the whole bodies of estuarine bait fish (common mummichog) averaged 708 ng/g wet wt.
\nPCBs that pass from the Neponset River to the Neponset River Estuary are either dissolved or associated with particulate matter (including living and nonliving material) suspended in the water column. A small proportion of PCBs may also be transported as part of the body burden of fish and wildlife. During the period May 13, 2005 to April 28, 2006, about 5,100 g (3.8 L or 1 gal) of PCBs were transported from the Neponset River to the Neponset River Estuary. Generally, about one-half of these PCBs were dissolved in the water column and the other half were associated with particulate matter; however, the proportion that was either dissolved or particulate varied seasonally. Most PCBs transported from the river to the estuary are composed of four or fewer chlorine atoms per biphenyl molecule.
\nThe data suggest that widespread PCB contamination of the lower Neponset River originated from Mother Brook, a Neponset River tributary, starting sometime around the early 1950s or earlier. In 1955, catastrophic dam failure caused by flooding likely released PCB-contaminated sediment downstream and into the Neponset River Estuary. PCBs from this source area likely continued to be released after the flood and during subsequent rebuilding of downstream dams. Today (2007), PCBs are mostly trapped behind these dams; however, some PCBs either diffuse or are entrained back into the water column and are transported downstream by river water into the estuary or volatilize into the atmosphere. In addition to the continuing release of PCBs from historically contaminated bottom sediment, PCBs are still (2007) originating from source areas along Mother and Meadow Brook as well as other sources along the river and Boston Harbor. PCBs from the river (transported by river water) and from the harbor (transported by tidal action) appear to have contaminated parts of the Neponset River Estuary.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115004","collaboration":"Prepared in cooperation with the Massachusetts Department of Fish and Game, Division of Ecological Restoration, Riverways Program","usgsCitation":"Breault, R., 2011, Concentrations, loads, and sources of polychlorinated biphenyls, Neponset River and Neponset River Estuary, eastern Massachusetts (Originally posted June 8, 2011; Version 1.1: June 24, 2014): U.S. Geological Survey Scientific Investigations Report 2011-5004, Report: x, 143 p.; Appendixes 1-5, https://doi.org/10.3133/sir20115004.","productDescription":"Report: x, 143 p.; Appendixes 1-5","numberOfPages":"157","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":116612,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5004.jpg"},{"id":21858,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5004/","linkFileType":{"id":5,"text":"html"}},{"id":289031,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2011/5004/pdf/sir2011-5004_appx2_508.pdf"},{"id":289029,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5004/pdf/sir2011-5004.pdf"},{"id":289030,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2011/5004/pdf/sir2011-5004_appx1_508.pdf"},{"id":289032,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2011/5004/pdf/sir2011-5004_appx3_508.pdf"},{"id":289033,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2011/5004/pdf/sir2011-5004_appx4_508.pdf"},{"id":289034,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2011/5004/pdf/sir2011-5004_appx5_508.pdf"}],"projection":"Lambert conformal conic projection","datum":"North American Datum of 1983","country":"United States","state":"Massachusetts","otherGeospatial":"Neponset River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.333333,42.166667 ], [ -71.333333,42.333333 ], [ -71.0,42.333333 ], [ -71.0,42.166667 ], [ -71.333333,42.166667 ] ] ] } } ] }","edition":"Originally posted June 8, 2011; Version 1.1: June 24, 2014","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53b7b0d5e4b0388651d9168e","contributors":{"authors":[{"text":"Breault, Robert F. 0000-0002-2517-407X rbreault@usgs.gov","orcid":"https://orcid.org/0000-0002-2517-407X","contributorId":2219,"corporation":false,"usgs":true,"family":"Breault","given":"Robert F.","email":"rbreault@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":350803,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70159491,"text":"70159491 - 2011 - Remote sensing of soil moisture using airborne hyperspectral data","interactions":[],"lastModifiedDate":"2015-11-12T12:08:37","indexId":"70159491","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1722,"text":"GIScience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing of soil moisture using airborne hyperspectral data","docAbstract":"Landscape assessment of soil moisture is critical to understanding the hydrological cycle at the regional scale and in broad-scale studies of biophysical processes affected by global climate changes in temperature and precipitation. Traditional efforts to measure soil moisture have been principally restricted to in situ measurements, so remote sensing techniques are often employed. Hyperspectral sensors with finer spatial resolution and narrow band widths may offer an alternative to traditional multispectral analysis of soil moisture, particularly in landscapes with high spatial heterogeneity. This preliminary research evaluates the ability of remotely sensed hyperspectral data to quantify soil moisture for the Little River Experimental Watershed (LREW), Georgia. An airborne hyperspectral instrument with a short-wavelength infrared (SWIR) sensor was flown in 2005 and 2007 and the results were correlated to in situ soil moisture values. A significant statistical correlation (R 2 value above 0.7 for both sampling dates) for the hyperspectral instrument data and the soil moisture probe data at 5.08 cm (2 inches) was determined. While models for the 20.32 cm (8 inches) and 30.48 cm (12 inches) depths were tested, they were not able to estimate soil moisture to the same degree.
","language":"English","publisher":"Taylor and Francis","doi":"10.2747/1548-1603.48.4.522","usgsCitation":"Finn, M.P., Lewis, M., Bosch, D.D., Giraldo, M., Yamamoto, K.H., Sullivan, D.G., Kincaid, R., Luna, R., Allam, G.K., Kvien, C., and Williams, M.S., 2011, Remote sensing of soil moisture using airborne hyperspectral data: GIScience and Remote Sensing, v. 48, no. 4, p. 522-540, https://doi.org/10.2747/1548-1603.48.4.522.","productDescription":"19 p.","startPage":"522","endPage":"540","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-027730","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":311209,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2013-05-15","publicationStatus":"PW","scienceBaseUri":"5645c64de4b0e2669b30f214","contributors":{"authors":[{"text":"Finn, Michael P. 0000-0003-0415-2194 mfinn@usgs.gov","orcid":"https://orcid.org/0000-0003-0415-2194","contributorId":2657,"corporation":false,"usgs":true,"family":"Finn","given":"Michael","email":"mfinn@usgs.gov","middleInitial":"P.","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":579210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lewis, Mark (David)","contributorId":149811,"corporation":false,"usgs":false,"family":"Lewis","given":"Mark (David)","affiliations":[],"preferred":false,"id":579666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bosch, David D.","contributorId":149812,"corporation":false,"usgs":false,"family":"Bosch","given":"David","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":579667,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Giraldo, Mario","contributorId":66094,"corporation":false,"usgs":true,"family":"Giraldo","given":"Mario","email":"","affiliations":[],"preferred":false,"id":579668,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yamamoto, Kristina H. khyamamoto@usgs.gov","contributorId":4490,"corporation":false,"usgs":true,"family":"Yamamoto","given":"Kristina","email":"khyamamoto@usgs.gov","middleInitial":"H.","affiliations":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"preferred":true,"id":579669,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sullivan, Dana G.","contributorId":149813,"corporation":false,"usgs":false,"family":"Sullivan","given":"Dana","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":579670,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kincaid, Russell","contributorId":149814,"corporation":false,"usgs":false,"family":"Kincaid","given":"Russell","email":"","affiliations":[],"preferred":false,"id":579671,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Luna, Ronaldo","contributorId":64970,"corporation":false,"usgs":true,"family":"Luna","given":"Ronaldo","email":"","affiliations":[],"preferred":false,"id":579672,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Allam, Gopala Krishna","contributorId":149815,"corporation":false,"usgs":false,"family":"Allam","given":"Gopala","email":"","middleInitial":"Krishna","affiliations":[],"preferred":false,"id":579673,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kvien, Craig","contributorId":33434,"corporation":false,"usgs":true,"family":"Kvien","given":"Craig","email":"","affiliations":[],"preferred":false,"id":579674,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Williams, Michael S.","contributorId":149816,"corporation":false,"usgs":false,"family":"Williams","given":"Michael","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":579675,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70121650,"text":"70121650 - 2011 - Multilocus phylogeography and population structure of common eiders breeding in North America and Scandinavia","interactions":[],"lastModifiedDate":"2021-03-31T13:30:07.436538","indexId":"70121650","displayToPublicDate":"2013-08-25T09:25:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Multilocus phylogeography and population structure of common eiders breeding in North America and Scandinavia","docAbstract":"Aim Glacial refugia during the Pleistocene had major impacts on the levels and spatial apportionment of genetic diversity of species in northern latitude ecosystems. We characterized patterns of population subdivision, and tested hypotheses associated with locations of potential Pleistocene refugia and the relative contribution of these refugia to the post-glacial colonization of North America and Scandinavia by common eiders (Somateria mollissima). Specifically, we evaluated localities hypothesized as ice-free areas or glacial refugia for other Arctic vertebrates, including Beringia, the High Arctic Canadian Archipelago, Newfoundland Bank, Spitsbergen Bank and north-west Norway.
Location Alaska, Canada, Norway and Sweden.
Methods Molecular data from 12 microsatellite loci, the mitochondrial DNA (mtDNA) control region, and two nuclear introns were collected and analysed for 15 populations of common eiders (n = 716) breeding throughout North America and Scandinavia. Population genetic structure, historical population fluctuations and gene flow were inferred using F-statistics, analyses of molecular variance, and multilocus coalescent analyses.
Results Significant inter-population variation in allelic and haplotypic frequencies were observed (nuclear DNA FST = 0.004–0.290; mtDNA ΦST = 0.051–0.927). Whereas spatial differentiation in nuclear genes was concordant with subspecific designations, geographic proximity was more predictive of inter-population variance in mitochondrial DNA haplotype frequency. Inferences of historical population demography were consistent with restriction of common eiders to four geographic areas during the Last Glacial Maximum: Belcher Islands, Newfoundland Bank, northern Alaska and Svalbard. Three of these areas coincide with previously identified glacial refugia: Newfoundland Bank, Beringia and Spitsbergen Bank. Gene-flow and clustering analyses indicated that the Beringian refugium contributed little to common eider post-glacial colonization of North America, whereas Canadian, Scandinavian and southern Alaskan post-glacial colonization is likely to have occurred in a stepwise fashion from the same glacial refugium.
Main conclusions Concordance of proposed glacial refugia used by common eiders and other Arctic species indicates that Arctic and subarctic refugia were important reservoirs of genetic diversity during the Pleistocene. Furthermore, suture zones identified at MacKenzie River, western Alaska/Aleutians and Scandinavia coincide with those identified for other Arctic vertebrates, suggesting that these regions were strong geographic barriers limiting dispersal from Pleistocene refugia.
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Lidar provides an extremely high level of regional topographic detail, which makes this technology an essential component of U.S. Geological Survey (USGS) science strategy. 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This combination of techniques has been used routinely by federal and state fishery management agencies for several decades as a reliable means to obtain quantitative data on trout populations or to describe fish community structure. In this paper we review the effects of electrofishing on fish and discuss this within the context of depletion sampling and multiple exposures of fishes to electric fields. The multiple wave forms most commonly used in sampling (alternating current, direct current, and pulsed direct current) are discussed as well as electrofishing induced response, injury and physiological stress. Fish that survive electrofishing injuries are more likely to suffer short and long-term adverse effects to their behavior, health, growth, or reproduction. Of greatest concern are the native, non-target species that may be subjected to multiple electrical shocks during the course of a 3-pass depletion survey. These exposures and their effects on the non-target species warrant further study as do the overall effects of electrofishing on populations and community structure.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Bridging America and Russia with shared perspectives on aquatic animal health: Proceedings of the Third Bilateral Conference between Russia and the United States","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Third Bilateral Conference Between Russia and the United States, Aquatic Animal Health 2009","conferenceDate":"July 12-20, 2009","conferenceLocation":"Shepherdstown, WV","language":"English","publisher":"Khaled bin Sultan Living Oceans Foundation","publisherLocation":"Landover, MD","isbn":"978-0-9835611-0-1","usgsCitation":"Panek, F.M., and Densmore, C.L., 2011, Electrofishing and the effects of depletion sampling on fish health: A review and recommendations for additional study, in Bridging America and Russia with shared perspectives on aquatic animal health: Proceedings of the Third Bilateral Conference between Russia and the United States, Shepherdstown, WV, July 12-20, 2009, p. 299-308.","productDescription":"10 p.","startPage":"299","endPage":"308","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":275408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275406,"type":{"id":11,"text":"Document"},"url":"https://www.lsc.usgs.gov/files/Panek%20%26%20Densmore%202011.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51f25420e4b0279fe2e1bffb","contributors":{"editors":[{"text":"Cipriano, R. 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M.","contributorId":51183,"corporation":false,"usgs":true,"family":"Panek","given":"F.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":481457,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Densmore, Christine L.","contributorId":18316,"corporation":false,"usgs":true,"family":"Densmore","given":"Christine","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":481456,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70047006,"text":"sim3183 - 2011 - Potentiometric surface of the upper Floridan aquifer, west-central Florida, May 2011","interactions":[],"lastModifiedDate":"2015-01-15T17:48:53","indexId":"sim3183","displayToPublicDate":"2013-01-01T12:52:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3183","title":"Potentiometric surface of the upper Floridan aquifer, west-central Florida, May 2011","docAbstract":"The Floridan aquifer system consists of the Upper and Lower Floridan aquifers separated by the middle confining unit. The middle confining unit and the Lower Floridan aquifer in west-central Florida generally contain highly mineralized water. The water-bearing units containing freshwater are herein referred to as the Upper Floridan aquifer. The Upper Floridan aquifer is the principal source of water in the Southwest Florida Water Management District and is used for major public supply, domestic use, irrigation, and brackish water desalination in coastal communities (Southwest Florida Water Management District, 2000). This map report shows the potentiometric surface of the Upper Floridan aquifer measured in May 2011. The potentiometric surface is an imaginary surface connecting points of equal altitude to which water will rise in tightly-cased wells that tap a confined aquifer system (Lohman, 1979). This map represents water-level conditions near the end of the dry season, when groundwater levels usually are at an annual low and withdrawals for agricultural use typically are high. The cumulative average rainfall of 45.74 inches for west-central Florida (from June 2010 through May 2011) was 6.85 inches below the historical cumulative average of 52.59 inches (Southwest Florida Water Management District, 2011). Historical cumulative averages are calculated from regional rainfall summary reports (1915 to most recent complete calendar year) and are updated monthly by the Southwest Florida Water Management District. This report, prepared by the U.S. Geological Survey in cooperation with the Southwest Florida Water Management District, is part of a semi-annual series of Upper Floridan aquifer potentiometric-surface map reports for west-central Florida. Potentiometric-surface maps have been prepared for January 1964, May 1969, May 1971, May 1973, May 1974, and for each May and September from 1975 through 2010. Water-level data are collected in May and September each year to show the approximate annual low and high water-level conditions, respectively. Most of the water-level data for this map were collected by the U.S. Geological Survey during the period May 23-27, 2011. Supplemental water-level data were collected by other agencies and companies. Most water-level measurements were made during a 5-day period; therefore, measurements do not represent a \"snapshot\" of conditions at a specific time, nor do they necessarily coincide with the seasonal low water-level condition.
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These archival products supplement direct access to current and historical water data provided by NWISWeb. Beginning with Water Year 2006, annual water data reports are available as individual electronic Site Data Sheets for the entire Nation for retrieval, download, and localized printing on demand. National distribution includes tabular and map interfaces for search, query, display and download of data. From 1962 until 2005, reports were published by State as paper documents, although most reports since the mid-1990s are also available in electronic form through this web page. Reports prior to 1962 were published in occasional USGS Water-Supply Papers and other reports.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/wdr2011","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2011, Water-resources data for the United States: water year 2011: U.S. Geological Survey Water Data Report 2011, HTML Document, https://doi.org/10.3133/wdr2011.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":634,"text":"Water Resources Program","active":false,"usgs":true}],"links":[{"id":269344,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/wdr2011.jpg"},{"id":269342,"type":{"id":15,"text":"Index Page"},"url":"https://wdr.water.usgs.gov/wy2011/search.jsp"},{"id":269343,"type":{"id":15,"text":"Index Page"},"url":"https://wdr.water.usgs.gov/"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5142f18de4b073a963ff6629","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":535455,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70041884,"text":"70041884 - 2011 - Population dynamics of Lake Ontario lake trout during 1985-2007","interactions":[],"lastModifiedDate":"2013-02-28T11:31:32","indexId":"70041884","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Population dynamics of Lake Ontario lake trout during 1985-2007","docAbstract":"Lake trout Salvelinus namaycush were extirpated from Lake Ontario circa 1950 owing to commercial and recreational fishing, predation by sea lampreys Petromyzon marinus, and habitat degradation. Since the 1970s, substantial efforts have been devoted to reestablishing a self-sustaining population through stocking, sea lamprey control, and harvest reduction. Although a stocking-supported population has been established, only limited natural reproduction has been detected. Since the 1990s, surveys have indicated a continuing decline in overall abundance despite fairly static stocking levels. We constructed a statistical catch-at-age model to describe the dynamics of Lake Ontario lake trout from 1985 to 2007 and explore what factor(s) could be causing the declines in abundance. Model estimates indicated that abundance had declined by approximately 76% since 1985. The factor that appeared most responsible for this was an increase in age-1 natural mortality rates from approximately 0.9 to 2.5 between 1985 and 2002. The largest source of mortality for age-2 and older fish was sea lamprey predation, followed by natural and recreational fishing mortality. Exploitation was low, harvest levels being uncertain and categorized by length rather than age. Accurate predictions of fishery harvest and survey catch per unit effort were obtained despite low harvest levels by using atypical data (e.g., numbers stocked as an absolute measure of recruitment) and a flexible modeling approach. Flexible approaches such as this might allow similar assessments for a wide range of lightly exploited stocks. The mechanisms responsible for declining age-1 lake trout survival are unknown, but the declines were coincident with an increase in the proportion of stocked fish that were of the Seneca strain and a decrease in the overall stocking rate. It is possible that earlier studies suggesting that Seneca strain lake trout would be successful in Lake Ontario are no longer applicable given the large ecosystem changes that have occurred subsequent to invasion by dreissenid mussels.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"North American Journal of Fisheries Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","publisherLocation":"Philadelphia, PA","doi":"10.1080/02755947.2011.635241","usgsCitation":"Brenden, T.O., Bence, J., Lantry, B.F., Lantry, J.R., and Schaner, T., 2011, Population dynamics of Lake Ontario lake trout during 1985-2007: North American Journal of Fisheries Management, v. 31, no. 5, p. 962-979, https://doi.org/10.1080/02755947.2011.635241.","productDescription":"18 p.","startPage":"962","endPage":"979","ipdsId":"IP-027372","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":268545,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/02755947.2011.635241"},{"id":268546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Lake Ontario","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.1171,43.0971 ], [ -80.1171,44.2941 ], [ -76.0817,44.2941 ], [ -76.0817,43.0971 ], [ -80.1171,43.0971 ] ] ] } } ] }","volume":"31","issue":"5","noUsgsAuthors":false,"publicationDate":"2011-11-29","publicationStatus":"PW","scienceBaseUri":"51308a96e4b04c194073ae2a","contributors":{"authors":[{"text":"Brenden, Travis O.","contributorId":13876,"corporation":false,"usgs":true,"family":"Brenden","given":"Travis","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":470299,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bence, James R.","contributorId":95026,"corporation":false,"usgs":false,"family":"Bence","given":"James R.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":470302,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lantry, Brian F. 0000-0001-8797-3910 bflantry@usgs.gov","orcid":"https://orcid.org/0000-0001-8797-3910","contributorId":3435,"corporation":false,"usgs":true,"family":"Lantry","given":"Brian","email":"bflantry@usgs.gov","middleInitial":"F.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":470298,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lantry, Jana R.","contributorId":28495,"corporation":false,"usgs":false,"family":"Lantry","given":"Jana","email":"","middleInitial":"R.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":470300,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schaner, Ted","contributorId":69939,"corporation":false,"usgs":true,"family":"Schaner","given":"Ted","email":"","affiliations":[],"preferred":false,"id":470301,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70045267,"text":"70045267 - 2011 - Observations of debris flows at Chalk Cliffs, Colorado, USA: Part 2, changes in surface morphometry from terrestrial laser scanning in the summer of 2009","interactions":[],"lastModifiedDate":"2013-07-05T09:31:44","indexId":"70045267","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2122,"text":"Italian Journal of Engineering Geology and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Observations of debris flows at Chalk Cliffs, Colorado, USA: Part 2, changes in surface morphometry from terrestrial laser scanning in the summer of 2009","docAbstract":"High resolution topographic data that quantify changes in channel form caused by sequential debris flows in natural channels are rare at the reach scale. Terrestrial laser scanning (TLS) techniques are utilized to capture morphological changes brought about by a high-frequency of debris-flow events at Chalk Cliffs, Colorado. The purpose of this paper is to compare and contrast the topographic response of a natural channel to the documented debris-flow events. TLS survey data allowed for the generation of high-resolution (2-cm) digital terrain models (DTM) of the channel. A robust network of twelve permanent control points permitted repeat scanning sessions that provided multiple DTM to evaluate fine-scale topographic change associated with three debris-flow events. Difference surfaces from the DTM permit the interpretations of spatial variations in channel morphometry and net volume of material deposited and eroded within and between a series of channel reaches. Each channel reach experienced erosion, deposition, and both net volumetric gains and losses were measured. Analysis of potential relationships between erosion and deposition magnitudes yielded no strong correlations with measures of channel-reach morphometry, suggesting that channel reach-specific predictions of potential erosion or deposition locations or rates cannot be adequately derived from statistical analyses of pre-event channel-reach morphometry.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Italian Journal of Engineering Geology and Environment: 5th International Conference on Debris-Flow Hazards Mitigation: Mechanics, Prediction and Assessment, Padua, Italy - 14-17 June 2011","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Casa Editrice Università La Sapienza","doi":"10.4408/IJEGE.2011-03.B-083","usgsCitation":"Staley, D.M., Wasklewicz, T.A., Coe, J.A., Kean, J.W., McCoy, S.W., and Tucker, G.E., 2011, Observations of debris flows at Chalk Cliffs, Colorado, USA: Part 2, changes in surface morphometry from terrestrial laser scanning in the summer of 2009: Italian Journal of Engineering Geology and Environment, p. 759-768, https://doi.org/10.4408/IJEGE.2011-03.B-083.","productDescription":"10 p.","startPage":"759","endPage":"768","ipdsId":"IP-024532","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":274481,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274480,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.4408/IJEGE.2011-03.B-083"}],"country":"United States","state":"Colorado","otherGeospatial":"Chalk Cliffs","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0603,36.9924 ], [ -109.0603,41.0034 ], [ -102.0409,41.0034 ], [ -102.0409,36.9924 ], [ -109.0603,36.9924 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d8136be4b0b0351701e194","contributors":{"authors":[{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":477168,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wasklewicz, Thad A.","contributorId":39275,"corporation":false,"usgs":true,"family":"Wasklewicz","given":"Thad","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":477170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":477166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":477167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCoy, Scott W.","contributorId":94954,"corporation":false,"usgs":true,"family":"McCoy","given":"Scott","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":477171,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tucker, Greg E.","contributorId":23422,"corporation":false,"usgs":true,"family":"Tucker","given":"Greg","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":477169,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70044418,"text":"70044418 - 2011 - USGS invasive species solutions","interactions":[],"lastModifiedDate":"2018-09-21T11:24:07","indexId":"70044418","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2837,"text":"Natural Selections","active":true,"publicationSubtype":{"id":10}},"title":"USGS invasive species solutions","docAbstract":"Land managers must meet the invasive species challenge every day, starting with identification of problem species, then the collection of best practices for their control, and finally the implementation of a plan to remove the problem. 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To provide context for such interpretation, the relevance of niche and neutral theories of biogeography and the continuum and classification approaches to biogeographic description are assessed. Two extensive studies of alpine tundra, from the Indian Peaks area, Colorado and Glacier National Park, Montana, are combined. The data are ordinated to describe relations. The pattern that emerges is one of a continuum of vegetation, but with the distinctions one might expect from distant sites. The relationships of the similarity of vegetation on all possible pairs of sites to the environmental differences and geographic distances are analyzed using Mantel correlations. Because distance and environmental differences in climate between the two sites are correlated, partial correlations are weak but still significant. More advanced analyses are suggested for this environment prior to interpretation of monitoring efforts such as GLORIA.
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The NASA Moderate Resolution Imaging Spectroradiometer (MODIS) Characterization Support Team, in collaboration with United States Geological Survey, Earth Resources Observation and Science Center, has previously demonstrated the use of African desert sites to monitor the long-term calibration stability of Terra MODIS and Landsat 7 (L7) Enhanced Thematic Mapper plus (ETM+). The current study focuses on evaluating the suitability of the Sonoran Desert test site for post-launch long-term radiometric calibration as well as cross-calibration purposes. Due to the lack of historical and on-going in situ ground measurements, the Sonoran Desert is not usually used for absolute calibration. An in-depth evaluation (spatial, temporal, and spectral stability) of this site using well calibrated L7 ETM+ measurements and local climatology data has been performed. The Sonoran Desert site produced spatial variability of about 3 to 5% in the reflective solar regions, and the temporal variations of the site after correction for view-geometry impacts were generally around 3%. 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